Sougwen Chung is an internationally renowned multi-disciplinary artist and researcher, whose work explores the dynamics of humans and systems. Chung is a former research fellow at MIT's Media Lab and a pioneer in the field of human-machine collaboration. In 2019, she was selected as the Woman of the Year in Monaco for achievement in the Arts & Sciences. For the uninitiated, what is human-machine collaboration? Sougwen Chung: Human-machine collaboration is a perspective of technology not as a tool, but as a collaborator.

Welcome to the episode 59 and the penultimate AI in Action podcast of 2019, the show where we break down the hype and explore the impact that Data Science, Machine Learning and Artificial Intelligence are making on our everyday lives. Powered by Alldus International, our goal is to share with you the insights of technologists and data science enthusiasts to showcase the excellent work that is being done within AI in the United States and Europe. Today's guest is Marco Braun, Transformation Lead at Akelius. Akelius provides Better Living by acquiring, upgrading and managing residential properties. Akelius upgrades residential units to a quality level with newly constructed apartments.

Core to human-centered AI is explainability. If a machine cannot explain its reasoning in a way that humans understand and on human terms, the AI isn't working for people. Researchers from Georgia Institute of Technology, Cornell University and the University of Kentucky recently published the results of teaching a machine to generate conversational explanations of its model's internal state and action data representations in real-time. They tested whether people like the machine to tell them how it made decisions, and what characteristics of explanations drove people's perceptions of explainability. Relatability is key to understandability – when an AI uses natural language to explain itself, people put themselves in the AI's shoes and evaluate understandability based on whether the AI gives the same reasons they would.

With the help of artificial intelligence, BP says it needs 40% fewer workers to keep its natural gas ... [ ] flowing in Wyoming. A visitor to one of BP's natural gas fields in Wyoming a few years ago might have noticed an odd sight: smartphones in plastic bags tied to pumps with zip ties. This was an early test of a multistate initiative by the oil giant to link a network of Wi-Fi sensors to an artificial intelligence system--one that now operates the Wamsutter field in Wyoming with far less human oversight than before. Artificial intelligence has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry's 150,000 U.S. workers. Giant energy companies like Shell and BP are investing billions to bring artificial intelligence to new refineries, oilfields and deepwater drilling platforms.

AX Semantics an artificial intelligence (AI)-powered, natural language generation (NLG) company said it could create AI-produced content in more than 110 languages. The Stuttgart-based company which launched in the US today, 12 December 2019 already works with hundreds of customers, including several Fortune 500 companies such as Deloitte for BSS reporting, Porsche and Nestlé. The demand for digital content continues to rise. And technology like AI is considered to be instrumental in helping companies keep pace. The global NLG market size is expected to reach $1,150.9

For India's online learners, 2019 was the "Year of AI." Artificial Intelligence (AI) emerged as the most popular subject among e-learners, accounting for nearly two million enrollments in the last year alone, according to online learning platform Coursera's latest learner trends released yesterday (Dec. The analysis included 45 million learners, including five million Indians, on the platform. AI became accessible to the masses with AI For Everyone, which was launched in February this year by deeplearning.ai, Taught by Ng himself, AI For Everyone is described as a "primer course, geared toward non-technical learners--from marketers and designers to financiers and CEOs." It was the fifth most popular Coursera course of the year globally, and the fourth most popular in India.

Those were some of the questions posed by John Zimmer, president and co-founder of U.S. rideshare firm Lyft, at the recent Rakuten Optimism 2019 conference in Yokohama, Japan. Lyft became the first ridesharing company to go public earlier this year when it completed an IPO with a valuation of $24 billion. It has also been pursuing autonomous driving technology: in partnership with Aptiv, Lyft recently notched 50,000 rides in Las Vegas in just a year, and has recently launched Waymo autonomous vehicles on the Lyft platform in Phoenix, Arizona. Against that background, Zimmer spoke about the future of transport with Mickey Mikitani, CEO of early Lyft investor, Rakuten. "We have to think about what is the right infrastructure to support (the future of transport)," Zimmer said during his second appearance at Optimism since speaking at the inaugural conference last year in San Francisco.

IDC's Fleming, calling this the "most interesting" finding of the study, explained that improving the speed of sensor data refresh combined with AI "expands an organization's ability to focus on immediate planning, while also quickly identifying and resolving operational problems. The combination produces greater agility and more efficiency." More generally, those who use AI this way broaden their toolset to address issues of supply and demand, product quality, merchandising and more, says Intel's Gadgil: "They're focusing on issues like productivity, but they're also looking for the next opportunities for transformation in their business…they're pushing their organizations to connect the dots and see how some of these new technologies can contribute."

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It feels as though 2019 has gone by in a flash, that said, it has been a year in which we have seen great advancement in AI application methods and technical discovery, paving the way for future development. We are incredibly grateful to have had the leading minds in AI & Deep Learning present their latest work at our summits in San Francisco, Boston, Montreal and more, so we thought we would share thirty of our highlight videos with you as we think everybody needs to see them!. We were delighted to be joined by Dawn at the Deep Reinforcement Learning Summit in June of 2019, presenting the latest industry research on Secure Deep Reinforcement Learning, covering both the lessons leant in the lead up to her presentation, current challenges faced for advancement, and the future direction of which her research is set to take. You can see Dawn's full presentation from June here. Reinforcement Learning is somewhat of a hotbed for research, this year alone we have seen several presentations that have broken down the ins and outs of RL, that said, Doina's talk just last month gave us some new angles on the latest algorithmic development.